Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves

Abstract

The increasing occurrence frequency of extreme temperature events, e.g., heat and cold waves, causes prolonged periods of low renewable production and increased load demand, threatening the power system energy balance. In this context, this paper proposes to quantify the energy imbalance in long-duration Hydrogen energy storage (HES)-assisted power systems under heat waves (HWs). First, we comprehensively model how HWs impact the operating characteristics of multiple grid components, including renewable generation, load, and dynamic thermal rating of transmission lines. Both exogenous prediction information and decision-dependent uncertainties (DDU) in demand response (DR) are properly modeled and taken into account. On this basis, we establish a quantification model for evaluating future energy imbalance in the presence of upcoming HWs in a two-stage stochastic framework, where the first stage determines the Hydrogen amount to be pre-stored before the heatwave, and the second stage comprises scenario-wise operation during the heatwave considering impacts of heatwaves on multiple components, DR, and available energy storage from HES. A Benders decomposition-based solution method is presented for the established two-stage stochastic model with DDU and mixed-binary recourse. Case studies on modified IEEE-6 bus and 118-bus systems verify the proposed model and solution method. Case study results show that the energy imbalance and operation costs due to HWs can be effectively decreased by pre-storing Hydrogen, implementing DDU-featured DR, and preserving more generator reserve capacity.

Keywords

• Benders decomposition (BD)
• Decision-dependent uncertainty (DDU)
• Heat waves (HWs)
• Hydrogen energy storage (HES)
• Resilient operation
• Two-stage stochastic optimization